Developing and enhancing statistical and machine learning models using structured and unstructured data to generate predictive insights and attributes
Design and building data pipelines and analytical solutions that support risk segmentation and insurance use cases
Providing actuarial expertise and recommendations to inform model development, risk segmentation, and support rate filings.
Researching and applying innovative data science methodologies to solve complex business problems
Managing and analyzing large, complex datasets, including data storage, processing, and quality assurance
Applying best practices for data validation, testing, and model performance monitoring
Collaborating with team members to share knowledge, strengthen capabilities, and contribute to a strong analytical culture
Identifying and leveraging new data sources to improve and validate existing models
Partnering with internal stakeholders to understand business needs, troubleshoot challenges, and deliver actionable insights
Maintaining a strong understanding of team tools, technologies, and evolving industry trends
Applying business and domain knowledge to drive effective, practical solutions
Communicating progress, insights, and outcomes clearly to stakeholders
Supporting team excellence by upholding high standards of quality, accountability, and execution

Minimum undergraduate degree in relevant field and 4+ years of relevant work experience
Or a master’s degree in a relevant field and 2+ years of relevant work experience
Or a PhD in a relevant field
Strong expertise in Python
Coding skills in R, SQL, ECL are a plus
Good foundation in actuarial science, including experience applying actuarial principles to pricing, risk segmentation, or model development
Strong foundation in statistical and mathematical modeling, including model assumptions, diagnostics, and interpretability
Extensive programming skills in Python and/or R, with extensive experience with their standard data manipulation and ML packages
Strong ability as a self-starter to learn new technologies (Pyspark, ECL, Azure/AWS ML Services) and to share cross-functional knowledge across the teams

Health Benefits: Comprehensive, multi-carrier program for medical, dental and vision benefits
Retirement Benefits: 401(k) with match and an Employee Share Purchase Plan
Wellbeing: Wellness platform with incentives, Employee Assistance and Time-off Programs
Short-and-Long Term Disability, Life and Accidental Death Insurance, Critical Illness, and Hospital Indemnity
Family Benefits, including bonding and family care leaves, adoption and surrogacy benefits
Health Savings, Health Care, Dependent Care and Commuter Spending Accounts

Senior Data Scientist

Key skills